Autonomous Air-Ground Vehicle Operations Optimization in Hazardous Environments: A Multi-Armed Bandit Approach

TL;DR

This paper introduces an adaptive decision-making framework for autonomous air-ground vehicles operating in hazardous environments, combining Bayesian sensing strategies with vehicle routing to improve hazard mitigation efficiency.

Contribution

It presents a novel integrated approach using Bayesian UCB and VRPP for adaptive coordination of UAVs and UGVs in uncertain, hazardous settings.

Findings

Reduces dispatch cycles by approximately 30% on average.

Enhances hazard detection and mitigation reliability.

Demonstrates effective uncertainty management in autonomous operations.

Abstract

Hazardous environments such as chemical spills, radiological zones, and bio-contaminated sites pose significant threats to human safety and public infrastructure. Rapid and reliable hazard mitigation in these settings often unsafe for humans, calling for autonomous systems that can adaptively sense and respond to evolving risks. This paper presents a decision-making framework for autonomous vehicle dispatch in hazardous environments with uncertain and evolving risk levels. The system integrates a Bayesian Upper Confidence Bound (BUCB) sensing strategy with task-specific vehicle routing problems with profits (VRPP), enabling adaptive coordination of unmanned aerial vehicles (UAVs) for hazard sensing and unmanned ground vehicles (UGVs) for cleaning. Using VRPP allows selective site visits under resource constraints by assigning each site a visit value that reflects sensing or cleaning priorities. Site-level hazard beliefs are maintained through a time-weighted Bayesian update. BUCB scores guide UAV routing to balance exploration and exploitation under uncertainty, while UGV routes are optimized to maximize expected hazard reduction under resource constraints. Simulation results demonstrate that our framework reduces the number of dispatch cycles to resolve hazards by around 30% on average compared to baseline dispatch strategies, underscoring the value of uncertainty-aware vehicle dispatch for reliable hazard mitigation.